Jun.-Prof. Dr.-Ing. Alexander Dockhorn
Leibniz Universität Hannover
Institut für Informationsverarbeitung
Appelstr. 9A
30167 Hannover
Germany
phone: +49 511 762-5046
fax: +49 511 762-5333
office location: room 1327A
Show recent publications only
  • Conference Contributions
    • Alexander Dockhorn
      Choosing Representation, Mutation, and Crossover in Genetic Algorithms
      IEEE Computational Intelligence Magazine, IEEE, Vol. 17, No. 4, pp. 52-53, November 2022
    • Linjie Xu, Jorge Hurtado-Grueso, Dominic Jeurissen, Diego Perez Liebana, Alexander Dockhorn
      Elastic Monte Carlo Tree Search State Abstraction for Strategy Game Playing
      2022 IEEE Conference on Games (CoG), IEEE, 2022
    • Lars Wagner, Christopher Olson, Alexander Dockhorn
      Generalizations of Steering - A Modular Design
      2022 IEEE Conference on Games (CoG), IEEE, pp. 1-4, 2022
    • Linjie Xu, Diego Perez-Liebana, Alexander Dockhorn
      Towards Applicable State Abstractions: a Preview in Strategy
      The Multi-disciplinary Conference on Reinforcement Learning and Decision Making (RLDM) - RL as a Model of Agency, pp. 1-7, 2022
    • Alexander Dockhorn, Jorge Hurtado-Grueso, Dominik Jeurissen, Linjie Xu, Diego Perez-Liebana
      Game State and Action Abstracting Monte Carlo Tree Search for General Strategy Game-Playing
      Proceedings of the 2021 IEEE Conference on Games (CoG), IEEE, pp. 1--8, August 2021
    • Alexander Dockhorn, Jorge Hurtado-Grueso, Dominik Jeurissen, Linjie Xu, Diego Perez-Liebana
      Portfolio Search and Optimization for General Strategy Game-Playing
      2021 IEEE Congress on Evolutionary Computation (CEC), IEEE, pp. 2085-2092, 2021
    • Diego Perez-Liebana, Cristina Guerrero-Romero, Alexander Dockhorn, Linjie Xu, Jorge Hurtado, Dominik Jeurissen
      Generating Diverse and Competitive Play-Styles for Strategy Games
      2021 IEEE Conference on Games (CoG), IEEE, pp. 1-8, 2021
    • Alexander Dockhorn, Sanaz Mostaghim, Martin Kirst, Martin Zettwitz
      Multi-Objective Optimization and Decision-Making in Context Steering
      2021 IEEE Conference on Games (CoG), IEEE, pp. 1-8, 2021
    • Alexander Dockhorn, Rudolf Kruse
      Forward Model Learning for Motion Control Tasks
      2020 IEEE 10th International Conference on Intelligent Systems (IS), pp. 1--5, Varna, Bulgaria, September 2020
    • Alexander Dockhorn, Simon Lucas
      Local Forward Model Learning for GVGAI Games
      IEEE Conference on Computational Intelligence and Games, CIG, pp. 716--723, August 2020
    • Raluca D. Gaina, Martin Balla, Alexander Dockhorn, Raul Montoliu, Diego Perez-Liebana
      Design and Implementation of TAG: A Tabletop Games Framework.
      arXiv:2009.12065, 2020
    • Diego Perez-Liebana, Alexander Dockhorn, Jorge Hurtado Grueso, Dominik Jeurissen
      The Design Of “Stratega”: A General Strategy Games Framework
      arXiv:2009.05643, pp. 1--7, 2020
    • Raluca D Gaina, Martin Balla, Alexander Dockhorn, Raul Montoliu, Diego Perez-liebana
      TAG : A Tabletop Games Framework
      Joint Proceedings of the AIIDE 2020 Workshops co-located with 16th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment (AIIDE 2020); CEUR Workshop Proceedings (2020), CEUR Workshop Proceedings, pp. 1--7, Worcester, 2020, edited by J. C. Osborn
    • Alexander Dockhorn, Jorge Hurtado Grueso, Dominik Jeurissen, Diego Perez-Liebana
      “Stratega”: A General Strategy Games Framework
      Joint Proceedings of the AIIDE 2020 Workshops co-located with 16th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment (AIIDE 2020); Artificial Intelligence for Strategy Games, CEUR Workshop Proceedings, pp. 1--7, Worcester, 2020, edited by Osborn, Joesph C.
    • Alexander Dockhorn, Tony Schwensfeier, Rudolf Kruse
      Fuzzy Multiset Clustering for Metagame Analysis
      Proceedings of the 11th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT 2019), Atlantis Press, pp. 536-543, August 2019
    • Alexander Dockhorn, Simon M Lucas, Vanessa Volz, Ivan Bravi, Raluca D Gaina, Diego Perez-Liebana
      Learning Local Forward Models on Unforgiving Games
      2019 IEEE Conference on Games (CoG), IEEE, August 2019
    • Simon M Lucas, Alexander and Volz Dockhorn, Raluca D Gaina, Ivan Bravi, Diego Perez-Liebana, Sanaz Mostaghim, Rudolf Kruse
      A Local Approach to Forward Model Learning: Results on the Game of Life Game
      2019 IEEE Conference on Games (CoG), IEEE, pp. 1--8, August 2019
    • Alexander Dockhorn, Sanaz Mostaghim
      Introducing the Hearthstone-AI Competition
      arXiv:1906.04238, pp. 1--4, May 2019
    • Alexander Dockhorn, Tim Tippelt, Rudolf Kruse
      Model Decomposition for Forward Model Approximation
      2018 IEEE Symposium Series on Computational Intelligence (SSCI), IEEE, pp. 1751--1757, November 2018
    • Alexander Dockhorn, Daan Apeldoorn
      Forward Model Approximation for General Video Game Learning
      Proceedings of the 2018 IEEE Conference on Computational Intelligence and Games (CIG’18), IEEE, p. 425–432, August 2018
    • Tim Sabsch, Christian Braune, Alexander Dockhorn, Rudolf Kruse
      Using a multiobjective genetic algorithm for curve approximation
      2017 IEEE Symposium Series on Computational Intelligence, SSCI 2017 - Proceedings, IEEE, pp. 1--6, January 2018
    • Alexander Dockhorn, Max Frick, Ünal Akkaya, Rudolf Kruse
      Predicting Opponent Moves for Improving Hearthstone AI
      17th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2018, Springer International Publishing, pp. 621--632, 2018, edited by Medina, Jesus; Ojeda-Aciego, Manuel; Verdegay, José
    • Alexander Dockhorn, Rudolf Kruse
      Detecting Sensor Dependencies for Building Complementary Model Ensembles
      Proceedings of the 28. Workshop Computational Intelligence, Dortmund, 29.-30. November 2018, KIT Scientific Publishing, pp. 217--234, 2018, edited by Hoffmann, Frank; Hüllermeier, Eyke; Mikut, Ralf
    • Alexander Dockhorn, Christoph Doell, Matthias Hewelt, Rudolf Kruse
      A decision heuristic for Monte Carlo tree search doppelkopf agents
      2017 IEEE Symposium Series on Computational Intelligence (SSCI), IEEE, pp. 1--8, November 2017
    • Alexander Dockhorn, Rudolf Kruse
      Combining cooperative and adversarial coevolution in the context of pac-man
      2017 IEEE Conference on Computational Intelligence and Games, CIG 2017, pp. 60--67, 2017
    • Alexander Dockhorn, Christian Braune, Rudolf Kruse
      Variable density based clustering
      2016 IEEE Symposium Series on Computational Intelligence (SSCI), IEEE, pp. 1--8, December 2016
    • Pascal Held, Alexander Dockhorn, Benjamin Krause, Rudolf Kruse
      Clustering Social Networks Using Competing Ant Hives
      2015 Second European Network Intelligence Conference, IEEE, pp. 67--74, September 2015
    • Pascal Held, Alexander Dockhorn, Rudolf Kruse
      On Merging and Dividing Social Graphs
      Journal of Artificial Intelligence and Soft Computing Research, Walter de Gruyter, Vol. 5, No. 1, pp. 23--49, January 2015
    • Alexander Dockhorn, Christian Braune, Rudolf Kruse
      An Alternating Optimization Approach based on Hierarchical Adaptations of DBSCAN
      2015 IEEE Symposium Series on Computational Intelligence (SSCI), IEEE, No. 2, pp. 749--755, 2015
    • Pascal Held, Alexander Dockhorn, Rudolf Kruse
      On Merging and Dividing of Barabasi-Albert-graphs
      2014 IEEE Symposium on Evolving and Autonomous Learning Systems (EALS), Vol. 444, 2014
    • Pascal Held, Alexander Dockhorn, Rudolf Kruse
      Generating Events for Dynamic Social Network Simulations
      Information Processing and Management of Uncertainty in Knowledge-Based Systems, Springer International Publishing, pp. 46--55, Cham, 2014, edited by Laurent, Anne; Strauss, Olivier; Bouchon-Meunier, Bernadette; Yager, Ronald R.
  • Journals
    • Alexander Dockhorn, Martin Kirst, Sanaz Mostaghim, Martin Wieczorek, Heiner Zille
      Evolutionary Algorithm for Parameter Optimization of Context Steering Agents
      IEEE Transactions on Games, IEEE, pp. 1-12, 2022
    • Alexander Dockhorn, Rudolf Kruse
      Modelheuristics for efficient forward model learning
      At-Automatisierungstechnik, De Gruyter, October 2021
    • Daan Apeldoorn, Alexander Dockhorn
      Exception-Tolerant Hierarchical Knowledge Bases for Forward Model Learning
      IEEE Transactions on Games, Vol. 13, No. 3, pp. 249-262, 2021
    • Alexander Dockhorn, Rudolf Kruse
      Fuzzy Modeling in Game AI
      Journal of Pure and Applied Mathematics, TWMS, Vol. 12, No. 1, pp. 54-68, 2021
    • Alexander Dockhorn, Rudolf Kruse
      Predicting Cards Using a Fuzzy Multiset Clustering of Decks
      International Journal of Computational Intelligence Systems (IJCIS), Atlantis Press, Vol. 13, No. 1, pp. 1207--1217, August 2020
  • Book Chapters
    • Alexander Dockhorn, Rudolf Kruse
      Balancing Exploration and Exploitation in Forward Model Learning
      Advances in Intelligent Systems Research and Innovation, Springer International Publishing, pp. 1--19, Cham, 2022, edited by Sgurev, Vassil; Jotsov, Vladimir; Kacprzyk, Janusz
    • Alexander Dockhorn, Rudolf Kruse
      State and Action Abstraction for Search and Reinforcement Learning Algorithms
      Artificial Intelligence in Control and Decision-making Systems, Springer International Publishing, pp. 1-18, 2022
    • Alexander Dockhorn, Chris Saxton, Rudolf Kruse
      Association Rule Mining for Unknown Video Games
      Fuzzy Approaches for Soft Computing and Approximate Reasoning: Theories and Applications, Springer Cham, pp. 257--270, October 2020, edited by Lesot, Marie-Jeanne; Marsala, Christophe
  • Technical Report
    • Alexander Dockhorn
      Dissertation: Prediction-based Search for Autonomous Game-Playing
      Otto von Guericke University Magdeburg, pp. 1--231, 2020
    • Alexander Dockhorn
      Master Thesis: Hierarchical Extensions and Cluster Validation Techniques for DBSCAN
      Otto von Guericke University Magdeburg, pp. 1-80, 2015
    • Alexander Dockhorn
      Bachelor Thesis: Computergestützte Analyse onkologischer Daten mithilfe Graphischer Modelle
      Otto von Guericke University of Magdeburg, pp. 1--80, April 2014